INVESTIGATION OF FOULING PROCESS FOR CONVECTIVE HEAT TRANSFER IN AN ANNULAR DUCT

Experimental and theoretical study is summarized of fouling process on heat transfer surface. An automatic monitoring system was set up to determine impact of fouling. Experiments were performed with artificial hard water as a working fluid at different conditions. Some important parameters including water temperature, wall temperature, flow velocity, water hardness and alkalinity were testified to make sure their influences on the fouling process on heat transfer surfaces. The ranges of water temperature, wall temperature, flow velocity and water hardness are between 20～50℃, 50～75℃, 0.5～2.0m/s, 200 ～ 1000mg/L (as CaCO3), respectively. All the experimental data were recorded continuously and the fouling resistances were calculated accordingly. Furthermore, an analysis was conducted to understand mechanism of fouling on heat transfer surface according a new physical model of fouling process. Good agreements can be observed between calculated results and experimental data

Fast Bayesian inference in large Gaussian graphical models

Despite major methodological developments, Bayesian inference in Gaussian graphical models remains challenging in high dimension due to the tremendous size of the model space. This article proposes a method to infer the marginal and conditional independence structures between variables by multiple testing, which bypasses the exploration of the model space. Specifically, we introduce closed-form Bayes factors under the Gaussian conjugate model to evaluate the null hypotheses of marginal and conditional independence between variables. Their computation for all pairs of variables is shown to be extremely efficient, thereby allowing us to address large problems with thousands of nodes as required by modern applications. Moreover, we derive exact tail probabilities from the null distributions of the Bayes factors. These allow the use of any multiplicity correction procedure to control error rates for incorrect edge inclusion. We demonstrate the proposed approach on various simulated examples as well as on a large gene expression data set from The Cancer Genome Atlas.This research was supported by the Medical Research Council core funding number MRC MC UP 0801/and grant number MR/M004421

INVESTIGATION OF FOULING PROCESS FOR CONVECTIVE HEAT TRANSFER IN AN ANNULAR DUCT

Experimental and theoretical study is summarized of fouling process on heat transfer surface. An automatic monitoring system was set up to determine impact of fouling. Experiments were performed with artificial hard water as a working fluid at different conditions. Some important parameters including water temperature, wall temperature, flow velocity, water hardness and alkalinity were testified to make sure their influences on the fouling process on heat transfer surfaces. The ranges of water temperature, wall temperature, flow velocity and water hardness are between 20～50℃, 50～75℃, 0.5～2.0m/s, 200 ～ 1000mg/L (as CaCO3), respectively. All the experimental data were recorded continuously and the fouling resistances were calculated accordingly. Furthermore, an analysis was conducted to understand mechanism of fouling on heat transfer surface according a new physical model of fouling process. Good agreements can be observed between calculated results and experimental data

Softening Transitions with Quenched 2D Gravity

We perform extensive Monte Carlo simulations of the 10-state Potts model on quenched two-dimensional $\Phi^3$ gravity graphs to study the effect of quenched connectivity disorder on the phase transition, which is strongly first order on regular lattices. The numerical data provides strong evidence that, due to the quenched randomness, the discontinuous first-order phase transition of the pure model is softened to a continuous transition.Comment: 3 pages, LaTeX + 1 postscript figure. Talk presented at LATTICE96(other models). See also http://www.cond-mat.physik.uni-mainz.de/~janke/doc/home_janke.htm

Human cones appear to adapt at low light levels: Measurements on the red—green detection mechanism

AbstractRecent physiological evidence suggests that cones do not light adapt at low light levels. To assess whether adaptation is cone-selective at low light levels, the red-green detection mechanism was isolated. Thresholds were measured with a large test flash, which stimulated the L and M cones in different fixed amplitude ratios, on different colored adapting fields. Thresholds were plotted in L and M cone contrast coordinates. The red-green mechanism responded to an equally-weighted difference of L and M cone contrast on each colored field, demonstrating equivalent, Weberian adaptation of the L and M cone signals. The L and M cone signals independently adapted for illuminance levels as low as 60 effective trolands (e.g. M-cone trolands. Since this adaptation is entirely selective to cone type, it suggests that the cones themselves light-adapt. The red-green detection contour on reddish fields was displaced further out from the origin of the cone contrast coordinates, revealing an additional sensitivity loss at a subsequent, spectrally-opponent site. This second-site effect may arise from a net “red” or “green” signal that represents the degree to which the L and M cones are differently hyperpolarized by the steady, colored adapting field. Such differential hyperpolarization is compatible with equivalent, Weberian adaptation of the L and M cones

Capture of CO2 from Coal-fired Power Plant with NaOH Solution in a Continuous Pilot-scale Bubble-column Scrubber

AbstractA continuous pilot-scale bubble-column scrubber with NaOH as the absorbent was used to explore the capture of CO2 gas from a coal-fired power plant. The experimental design was based on the results of previous study. The diameter of the column was 20cm and the height of the column was 2.4 m. According to the S/N ratio, parameters, including absorption rate (RA), absorption efficiency (E), overall mass-transfer coefficient (KGa) and ratio of the gas-liquid flow rate (R), were selected for Taguchi analysis to obtain optimum conditions. A total of eleven experiments were carried out to verify the optimum conditions here. The range of the gas-flow rate (Qg) and liquid-flow rate (QLT) conducted in this work were 48-192 L/min and 1.6-10 L/min, respectively. The input gas concentrations were 9-12.2%. Using a steady-state material balance with a two-film model, RA and KGa could be determined. The results showed that E, RA and KGa were in the range of 30-98%, 1.03x10-4-11.48x10-4mol/s-L and 0.018-0.058 1/s, respectively. The obtained scrubbing factors (φ) were 0.00285-0.146mol/mol-L, while R was in the range of 0.23-24.14. The dynamic behavior of the scrubber was also discussed in this study. The results could be used as a basis for commercial scale operation for the carbon capture at a power plant as well as microalgae cultivation

Two charged strangeonium-like structures observable in the Y(2175)→ϕ(1020)π+π−Y(2175) \to \phi(1020)\pi^{+} \pi^{-} process

Via the Initial Single Pion Emission (ISPE) mechanism, we study the $\phi(1020)\pi^{+}$ invariant mass spectrum distribution of $Y(2175) \to \phi(1020)\pi^{+} \pi^{-}$. Our calculation indicates there exist a sharp peak structure ($Z_{s1}^+$) close to the $K\bar{K}^\ast$ threshold and a broad structure ($Z_{s2}^+$) near the $K^\ast\bar{K}^\ast$ threshold. In addition, we also investigate the $\phi(1680) \to \phi(1020)\pi^{+} \pi^{-}$ process due to the ISPE mechanism, where a sharp peak around the $K\bar{K}^\ast$ threshold appears in the $\phi(1020)\pi^{+}$ invariant mass spectrum distribution. We suggest to carry out the search for these charged strangeonium-like structures in future experiment, especially Belle II, Super-B and BESIII.Comment: 7 pages, 5 figures. Accepted by Eur. Phys. J.

Intelligent tracking control of a DC motor driver using self-organizing TSK type fuzzy neural networks

[[abstract]]In this paper, a self-organizing Takagi–Sugeno–Kang (TSK) type fuzzy neural network (STFNN) is proposed. The self-organizing approach demonstrates the property of automatically generating and pruning the fuzzy rules of STFNN without the preliminary knowledge. The learning algorithms not only extract the fuzzy rule of STFNN but also adjust the parameters of STFNN. Then, an adaptive self-organizing TSK-type fuzzy network controller (ASTFNC) system which is composed of a neural controller and a robust compensator is proposed. The neural controller uses an STFNN to approximate an ideal controller, and the robust compensator is designed to eliminate the approximation error in the Lyapunov stability sense without occurring chattering phenomena. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived to speed up the convergence rates of the tracking error. Finally, the proposed ASTFNC system is applied to a DC motor driver on a field-programmable gate array chip for low-cost and high-performance industrial applications. The experimental results verify the system stabilization and favorable tracking performance, and no chattering phenomena can be achieved by the proposed ASTFNC scheme.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子